Wan Nor Syuhada Wan Zahari, Eko Supriyanto, Nazriah Mahmud
The purpose of this study is to improve the existing stroke risk prediction model for the next 10 years. Current existing risk prediction model was done based on the data obtained mostly from America and Africa. There are a few risk prediction models done based on the data from Asian participants. Hence, this paper will predict the risk for stroke for the next 10 years using data collected from Asia. Data from Korean and China risk prediction model were obtained and sorted according to categories. The weightage of each risk factors is then calculated. This study also used the artificial intelligence as a comparison to predict the risk of stroke. Data from a few studies obtained and compared to estimate the probability of stroke that may occur in 10 years of time. Then, a set of data will be used to train the Artificial Neural Network (ANN) and compared to the results obtained using conventional calculation method. The usage of ANN to predict and learn about the risk factors for stroke will give a significant benefit in the future. This study developed a personalized stroke risk prediction which expected to be better and relevant to Asian people compared to other risk prediction model.
ANN, Prediction, Risk, Stroke
Cite this paper
Wan Nor Syuhada Wan Zahari, Eko Supriyanto, Nazriah Mahmud. (2019) Stroke Risk Prediction Model. International Journal of Biology and Biomedicine, 4, 1-6